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model = dict(
type='DBNet',
backbone=dict(
type='mmdet.ResNet',
depth=18,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=-1,
norm_cfg=dict(type='BN', requires_grad=True),
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet18'),
norm_eval=False,
style='caffe'),
neck=dict(
type='FPNC', in_channels=[64, 128, 256, 512], lateral_channels=256),
bbox_head=dict(
type='DBHead',
in_channels=256,
loss=dict(type='DBLoss', alpha=5.0, beta=10.0, bbce_loss=True),
postprocessor=dict(type='DBPostprocessor', text_repr_type='quad')),
train_cfg=None,
test_cfg=None)